基于小波变换的传感器故障检测技术研究

介绍了小波变换的基本理论及小波技术用于传感器故障检测的基本原理，给出了传感器故障检测方法，仿真实例证明了这一技术的有效性。     

直线电机车辆牵引电机恒隙控制的初步研究

直线电机轨道车辆采用直线感应电机牵引、轮轨系统支撑导向,是一种新型城市轨道交通工具。本文介绍了直线电机的原理,对加拿大、日本以及广州4号线的直线电机车辆的不同牵引电机悬挂方式进行了对比分析,提出了在牵引电机悬挂系统中采用主动控制的恒隙技术的初步设想。     

直线电机地铁车辆转向架

介绍了直线电机地铁车辆转向架的功能和组成、径向转向架的采用、直线感应电机悬挂技术、直线感应电机气隙调节装置,最后提出了目前直线电机地铁车辆转向架设计建议。     

基于正交基神经网络的热敏电阻温度传感器非线性补偿方法

针对热敏电阻温度传感器应用中存在的非线性问题，提出了应用正交基（0BF）神经网络进行非线性补偿的方法。研究结果表明，OBF神经网络非线性补偿算法具有补偿精度高、计算量小的优点，因而是一种有效的非线性补偿方法。     

不同级配对沥青混合料矿料间隙率的影响

沥青混合料矿料间隙率过大或过小都会对沥青混合料的路用性能产生不利影响。矿料间隙率对沥青混合料强度、耐久性和高温稳定性有很高的敏感度，是沥青混合料设计的一个重要参数之一。主要研究了不同级配对矿料间隙率的影响，通过马歇尔正交试验分析了级配对沥青混合料AC-13矿料间隙率的影响，得出了矿料间隙率与贝雷法评价级配的参数的关系。     

Nonlinear feedforward–feedback control of clutch-to-clutch shift technique

To improve the shift quality of the vehicle with clutch-to-clutch gear shifts, a nonlinear feedforward–feedback control scheme is proposed for clutch slip control during the shift inertia phase. The feedforward control is designed based on flatness in consideration of the system nonlinearities, and the linear feedback control is given to accommodate the model errors and the disturbances. Lookup tables, which are widely used to represent complex nonlinear characteristics of powertrain systems, appear in their original form in the designed feedforward controller, while the linear feedback controller is calculated through linear matrix inequalities such that the control system is robust against the parameter uncertainties. Finally, the designed controller is tested on an AMESim powertrain simulation model, which contains a time-variant model of clutch actuators.     

LAPPED TRANSFORM DOMAIN INTERFERENCE EXCISION USING MODIFIED MEDIAN FILTER

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直线电机车辆集电靴升靴故障分析及改进建议

针对直线电机车辆集电靴正线不能升靴的故障现象,分析了故障发生的原因。从工作原理和作业规程出发,提出加装集电靴人工升靴装置改进建议并优化作业流程。即:在新线车辆设计时增加导电靴升靴功能,对既有车辆不建议进行改造。对于现有列车在正线停放,建议列车保持升靴状态的方法简单可行。     

Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China

To improve predictive accuracy, new hybrid models are proposed for container throughput forecasting based on wavelet transforms and data characteristic analysis (DCA) within a decomposition-ensemble methodology. Because of the complexity and nonlinearity of the time series of container throughputs at ports, the methodology decomposes the original time series into several components, which are rather simpler sub-sequences. Consequently, difficult forecasting tasks are simplified into a number of relatively easier subtasks. In this way, the proposed hybrid models can improve the accuracy of forecasting significantly. In the methodology, four main steps are involved: data decomposition, component reconstruction based on the DCA, individual prediction for each reconstructed component, and ensemble prediction as the final output. An empirical analysis was conducted for illustration and verification purposes by using time series of container throughputs at three main ports in Bohai Rim, China. The results suggest that the proposed hybrid models are able to forecast better than do other benchmark models. Forecasting may facilitate effective real-time decision making for strategic management and policy drafting. Predictions of container throughput can help port managers make tactical and operational decisions, such as operations planning in ports, the scheduling of port equipment, and route optimization.     

基于精细积分算法的动荷载识别研究

为深入探讨动荷载识别问题,基于精细积分法的基本原理,针对单自由度和多自由度体系,假定外荷载在离散时间步长的微小时间间隔内按线性规律变化,推导出一种动载荷识别时域方法。通过实例分析了该法对不同类型荷载进行识别的效果。结果表明:该法对于稳态荷载以及随机荷载均是适用的,具有很好的稳定性、一定的抗噪能力、且计算精度较高,计算量较小,便于工程应用。